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Title: Quantitative SARS-CoV-2 alpha variant B.1.1.7 tracking in wastewater by allele-specific RT-qPCR
Authors: Lee, Wei Lin
Imakaev, Maxim
Armas, Federica
McElroy, Kyle A.
Gu, Xiaoqiong
Duvallet, Claire
Chandra, Franciscus
Chen, Hongjie
Leifels, Mats
Mendola, Samuel
Floyd-O'Sullivan, Róisín
Powell, Morgan M.
Wilson, Shane T.
Berge, Karl L. J.
Lim, Claire Y. J.
Wu, Fuqing
Xiao, Amy
Moniz, Katya
Ghaeli, Newsha
Matus, Mariana
Thompson, Janelle R.
Alm, Eric J.
Keywords: Engineering::Environmental engineering
Issue Date: 2021
Source: Lee, W. L., Imakaev, M., Armas, F., McElroy, K. A., Gu, X., Duvallet, C., Chandra, F., Chen, H., Leifels, M., Mendola, S., Floyd-O'Sullivan, R., Powell, M. M., Wilson, S. T., Berge, K. L. J., Lim, C. Y. J., Wu, F., Xiao, A., Moniz, K., Ghaeli, N., ...Alm, E. J. (2021). Quantitative SARS-CoV-2 alpha variant B.1.1.7 tracking in wastewater by allele-specific RT-qPCR. Environmental Science and Technology Letters, 8(8), 675-682.
Project: NRF2019-THE001-0003a 
Journal: Environmental Science and Technology Letters 
Abstract: The critical need for surveillance of SARS-CoV-2 variants of concern has prompted the development of methods that can track variants in wastewater. Here, we develop and present an open-source method based on allele-specific RT-qPCR (AS RT-qPCR) that detects and quantifies the B.1.1.7 variant, targeting spike protein mutations at three independent genomic loci that are highly predictive of B.1.1.7 (HV69/70del, Y144del, and A570D). Our assays can reliably detect and quantify low levels of B.1.1.7 with low cross-reactivity, and at variant proportions down to 1% in a background of mixed SARS-CoV-2. Applying our method to wastewater samples from the United States, we track the occurrence of B.1.1.7 over time in 19 communities. AS RT-qPCR results align with clinical trends, and summation of B.1.1.7 and wild-Type sequences quantified by our assays matches SARS-CoV-2 levels indicated by the U.S. CDC N1 and N2 assays. This work paves the way for AS RT-qPCR as a method for rapid inexpensive surveillance of SARS-CoV-2 variants in wastewater.
ISSN: 2328-8930
DOI: 10.1021/acs.estlett.1c00375
Schools: Asian School of the Environment 
Organisations: Campus for Research Excellence and Technological Enterprise (CREATE)
Research Centres: Singapore Centre for Environmental Life Sciences and Engineering (SCELSE) 
Rights: © 2021 The Authors. Published by American Chemical Society. This is an open-access article distributed under the terms of the Creative Commons Attribution License.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ASE Journal Articles
SCELSE Journal Articles

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